Peptide biomarkers of cardiovascular disease

ABSTRACT

The presently-disclosed subject matter provides methods for diagnosing a cardiovascular disease in a subject by determining an amount of one or more peptide biomarkers disclosed herein in a biological sample from the subject. The presently-disclosed subject matter further provides methods for determining treatment efficacy and/or progression of a cardiovascular disease in a subject by measuring amounts of one or more of the biomarkers in a biological sample from the subject. The presently-disclosed subject matter also provides antibodies and kits for measuring the biomarkers.

RELATED APPLICATIONS

The present application is a continuation-in-part application of U.S.application Ser. No. 12/596,814, filed Oct. 20, 2009 as a national stageentry of International Application No. PCT/US08/60879, filed Apr. 18,2008, and claiming the benefit of U.S. Provisional Patent ApplicationSer. No. 60/913,069, filed Apr. 20, 2007; U.S. Provisional PatentApplication Ser. No. 60/970,121, filed Sep. 5, 2007; and U.S.Provisional Patent Application Ser. No. 60/970,369, filed Sep. 6, 2007;the disclosures of each of which is incorporated herein by reference intheir entireties.

TECHNICAL FIELD

The presently disclosed subject matter relates to methods for diagnosingcardiovascular disease in a subject. In particular, the presentlydisclosed subject matter relates to methods for diagnosingcardiovascular disease in a subject by determining amounts of one ormore peptide biomarkers in a biological sample from the subject.

BACKGROUND

Cardiovascular diseases (CVDs) are debilitating illnesses that afflictmillions of people in the world each year. Indeed, in 1997, over 450,000people in the U.S. alone died from myocardial infarctions; one of everyfive deaths in that calendar year. In addition to myocardial infarction,cardiovascular diseases result in hypertension, angina,arteriosclerosis, and atherosclerosis. Angina, for example, accounts formore than 1 million hospital admissions annually in the U.S., and 6-8percent of subjects with this condition either have non-fatal myocardialinfarction, or die, within the first year after diagnosis.

Cardiovascular diseases are also a major cause of morbidity andmortality in subsets of the population already suffering from otherdisorders. For example, cardiovascular disease are the major cause ofmortality in end-stage renal disease (ESRD) subjects (1). Coronaryartery disease (CAD) is reported to occur in 40-60% of incidenthemodialysis subjects and this figure rises to more than 50% fordiabetic hemodialysis subjects (1-3). The annual incidence of newcoronary artery disease in dialysis subjects is 30-40 times higher thanin the general population (4). The rate at which hemodialysis subjectsin the United States are hospitalized for their first acute coronaryevent (myocardial infarction or unstable angina) is 2.9-3.3 per 100subject-years (5) and the annual overall mortality and cardiac mortalityfollowing acute myocardial infarction were 62% and 42%, respectively,between 1990 and 1995 (6). Moreover, hemodialysis subjects aresignificantly less likely to be evaluated with cardiac catheterizationand therefore have a lower incidence of coronary revascularizationprocedures (7).

Hence, the ability to accurately identify subjects with CVDs in thegeneral population, as well as in subpopulations identified as at highrisk for CVDs, such as the ESRD population, is of great importance.

Currently, physicians are able to diagnose CVD in subjects who havealready begun to experience symptoms. For example, the levels of certaincardiac-associated enzymes, such as creatine kinase, are elevated aftermyocardial infarction, and may be detected an enzyme-specific assay.Likewise, coronary angiography is the definitive means of diagnosingCAD. However, it is an expensive and invasive procedure. Algorithms havebeen developed for non-invasively assessing the risk of CAD in thegeneral population. These algorithms are based on well-established riskfactors, including dyslipidemia, smoking, hypertension and diabetes.While studies show that at least one of these risk factors is present in80-90% of subjects with coronary artery disease in the generalpopulation, it has been estimated that they explain only about 75% ofthe occurrence of CAD. Further, traditional risk factors for CAD derivedfrom studies of the normal population have limited applicability in atrisk subpopulations, such as for example hemodialysis subjects. Theprevalence of dyslipidemia, hypertension, diabetes and left ventricularhypertrophy is higher in hemodialysis subjects than in the generalpopulation and the relationship between some of these traditional riskfactors and cardiovascular outcomes appears to be different inhemodialysis subjects than it is in the normal population. For example,the relationship of both hypertension and cholesterol to coronary heartdisease and mortality is U-shaped in hemodialysis subjects, with higherblood pressures and cholesterol concentrations conferring a survivaladvantage (8, 9).

CVD constitutes a considerable medical and economic burden. Currentdiagnostic approaches are either invasive, expensive, associated withthe risk of complications, or their interpretation is confounded byconcurrent medical conditions. Alternative, non-invasive approaches areneeded that address these limitations. Thus, there is currently an unmetneed for new, more specific biomarkers of CVD that can be used toidentify subjects suffering from (even if physiologically asymptomatic)or at risk of CVD for targeted interventions.

SUMMARY

This Summary lists several embodiments of the presently disclosedsubject matter, and in many cases lists variations and permutations ofthese embodiments. This Summary is merely exemplary of the numerous andvaried embodiments. Mention of one or more representative features of agiven embodiment is likewise exemplary. Such an embodiment can typicallyexist with or without the feature(s) mentioned; likewise, those featurescan be applied to other embodiments of the presently disclosed subjectmatter, whether listed in this Summary or not. To avoid excessiverepetition, this Summary does not list or suggest all possiblecombinations of such features.

In some embodiments of the presently-disclosed subject matter, a methodfor diagnosing a cardiovascular disease in a subject is provided. Insome embodiments, the method comprises determining an amount of at leastone peptide having an amino acid sequence selected from SEQ ID NOS: 8-30in a biological sample from the subject and comparing the amount of theat least one peptide in the sample with a control level, wherein if theamount determined in the sample is different than the control level, thesubject is diagnosed as having, or at an increased risk of developing,the cardiovascular disease.

In some embodiments of the presently-disclosed subject matter, a methodfor determining treatment efficacy and/or progression of acardiovascular disease in a subject is provided. In some embodiments,the method comprises determining an amount of at least one peptidehaving an amino acid sequence selected from SEQ ID NOS: 8-30 in a firstbiological sample collected from the subject at a first time point;determining an amount of the at least one peptide in a second biologicalsample from the subject at a second time point; and comparing theamounts of the at least one peptide in the first and second samples,wherein a change in the amounts of the at least one peptide from thefirst and second samples is correlated with determining treatmentefficacy and/or progression of the cardiovascular disease in thesubject. In some embodiments, the first time point is prior toinitiation of a treatment for the cardiovascular disease and the secondtime point is after initiation of the treatment. In other embodiments,the first time point is prior to onset of the cardiovascular disease andthe second time point is after onset of the cardiovascular disease.

In some embodiments of the methods, the at least one peptide comprisesone or more peptides selected from the group consisting ofprotocadherin-20 (PCDH-20), tolloid-like 2 protein (TLL-2), mammaliantolloid protein (mTLD), bone morphogenetic protein-1 (BMP-1),phosphorylated fibrinopeptide A, chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2), andfragments thereof. In some embodiments, the at least one peptide is aplurality of peptides.

In some embodiments of the methods, determining the amount of the atleast one peptide comprises determining the amount of the at least onepeptide in the sample using mass spectrometry (MS) analysis (e.g.,matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF)MS analysis or electrospray ionization (ESI) MS), immunoassay analysis(e.g., enzyme-linked immunosorbent assay (ELISA)), or both.

In some embodiments of the methods, the at least one peptide is isolatedfrom a fraction of the sample selected from the group consisting of abound fraction and an unbound fraction. In some embodiments, the boundfraction is a an albumin-bound fraction or an immunoglobulin-boundfraction.

In some embodiments, the samples are independently selected from asaliva sample, a blood sample, a serum sample, a plasma sample, or aurine sample.

In some embodiments of the methods, the subject is human. In someembodiments the subject is a diabetic subject.

In some embodiments of the methods, the cardiovascular disease is acoronary artery disease (CAD) (e.g., atherosclerosis), a peripheralvascular disease, or both.

The presently-disclosed subject matter further provides methods fortreating a cardiovascular disease in a subject. In some embodiments, themethods comprise administering to the subject an effective amount of afibrinopeptide A polypeptide inhibitor molecule.

The presently-disclosed subject matter further provides antibodies orfragments thereof that specifically recognize a peptide having an aminoacid sequence selected from SEQ ID NOS: 8-30; a peptide associated witha peptide having an amino acid sequence selected from SEQ ID NOS: 8-30;or combinations thereof.

The presently-disclosed subject matter further provides kits fordetecting cardiovascular disease, or a risk thereof, in a subject. Insome embodiments, the kit comprises one or more antibodies thatspecifically recognize a peptide having an amino acid sequence selectedfrom SEQ ID NOS: 8-30; a peptide associated with a peptide having anamino acid sequence selected from SEQ ID NOS: 8-30; or combinationsthereof. In some embodiments, the one or more antibodies are a pluralityof different antibodies. In some embodiments, the antibodies are boundto a substrate. In some embodiments, the kit comprises instructions forusing the kit.

Accordingly, it is an object of the presently disclosed subject matterto measure peptide biomarkers of cardiovascular disease in a subject.This object is achieved in whole or in part by the presently disclosedsubject matter.

An object of the presently disclosed subject matter having been statedhereinabove, and which is achieved in whole or in part by the presentlydisclosed subject matter, other objects and advantages will becomeevident to those of ordinary skill in the art after a study of thefollowing description of the presently disclosed subject matter,figures, and non-limiting examples.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a graph showing multivariate analysis of peptide expressionusing principal components analysis (PCA). PCA scoring plot forcomparison of MALDI-TOF MS data developed from direct MS analysis offree, unbound serum peptides extracted from serum of subjects with CAD(circles) and subjects without CAD (squares). Unsupervised sorting ofsamples into groups indicates the variation in the data is a result ofdifferentially expressed serum peptides.

FIG. 2 is a graph showing average spectral intensities of awhole-serum-bound fragment of phosphorylated fibrinogen a chain (pFPA)(mass 1616.663 m/z; z=+1) in serum samples from subjects with andwithout CAD. Averaged spectral intensities (using total ion clusterarea) demonstrate increased expression of the pFPA peptide fragment inserum of subjects with CAD (CAD(+), right bar) as compared to subjectswithout CAD (CAD(−), left bar) (# p<0.025). Data are presented as meanand standard error.

FIG. 3 is a graph showing average spectral intensities for awhole-serum-bound fragment of chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2) (mass1991.892 m/z; z=+1) in serum samples from subjects with and without CAD.Averaged spectral intensities (using total ion cluster area) demonstratedecreased expression of the CSGalNAcT-2 peptide fragment in the serum ofsubjects with CAD (CAD(+), right bar) as compared to subjects withoutCAD (CAD(−), left bar) (# p<0.001). Data are presented as mean andstandard error.

FIG. 4 is a graph showing average spectral intensities for awhole-serum-bound fragment of tolloid-like 2 protein (TLL-2) or bonemorphogenetic protein-1 (BMP-1) (mass 1418.669 m/z; z=+1) in serumsamples from subjects with and without CAD. Averaged spectralintensities (using total ion cluster area) demonstrate increasedexpression of the BMP-1/TLL-2 fragment in the serum of subjects with CAD(CAD(+), right bar) as compared to subjects without CAD (CAD(−), leftbar (# p<0.025). Data are presented as mean and standard error.

FIGS. 5A and 5B show intact mTLD bound to serum proteins is increased inserum from subjects with CAD. Serum samples from subjects with CAD(CAD+, n=8) and without CAD (CAD−, n=9) were specifically immunodepletedof the 20 most abundant proteins using a ProteoPrep20 spin column. Thesehighly abundant proteins and co-immunodepleted proteins were eluted andanalyzed by 1D-PAGE and immunoblotting for mTLD expression. FIG. 5A is arepresentative immunoblot of the highly abundant serum protein fractionfor mTLD expression. FIG. 5B is a graph showing quantitativedensitometry of the immunoblot data. A statistically significant(*p<0.001) increased amount of mTLD was bound to highly abundantproteins in serum of subjects with CAD as compared to serum of subjectswithout CAD.

FIGS. 6A and 6B show intact (88 kDa) BMP-1 bound to highly abundantserum proteins is decreased in serum of subjects with CAD. Serum samplesfrom subjects with CAD (CAD+, n=8) and without CAD (CAD−, n=9) werespecifically immunodepleted of the 20 most abundant proteins using aProteoPrep20 spin column. These highly abundant proteins andco-immunodepleted proteins were eluted and analyzed by 1D-PAGE andimmunoblotting for BMP-1 expression. FIG. 6A is a representativeimmunoblot of the highly abundant serum protein fraction for BMP-1expression. Lanes 1-4 of FIG. 6A are serum from four different subjectswith CAD; Lanes 5-8 of FIG. 6A are samples from four different subjectswithout CAD; Lane 9 of FIG. 6A is pooled normal male serum, Lane 10 ofFIG. 6A is synthetic BMP-1 positive control, and Lane 11 of FIG. 6A isBioRad PRECISION PLUS™ prestained molecular weight standards. FIG. 6B isa graph showing quantitative densitometry of immunoblot data. Astatistically significant (# p<0.0001) increased amount of mature BMP-1was bound to highly abundant serum proteins in serum of subjects withoutCAD as compared to serum of subjects with CAD.

FIG. 7 is a flowchart showing candidate peptide biomarker discoveryworkflow. Serum samples were processed as described in the Methodssection of the Examples to yield four panels of peptides including freewhole serum peptides, free albumin/IgG depleted serum peptides, wholeserum protein bound peptides, and albumin/IgG bound peptides. Peptideprofiles for each of the four panels were compared using PCA and/orStudent's t-test with the goal of generating a listed of differentiallyexpressed peptide masses. Peptide sequence tags were generated usingMALDI-TOF/TOF MS and Matrix Science Mascot assisted MS analysis.

BRIEF DESCRIPTION OF THE TABLES

Table 1 shows demographic and biochemical characteristics of subjectswith and without CAD. Data are presented as mean±SD. No significantdifferences in these parameters were noted between two groups.

Table 2 shows serum peptides differentially expressed between subjectswith and without CAD. MALDI-TOF MS spectra were obtained, aligned, andcompared as described under the Methods section of the Examples.Differential expression was determined using Student's t-test aftermanual review of the primary MALDI-TOF MS data. There were nodifferences in the expression of peptides bound to albumin/IgG orreleased during albumin/IgG depletion.

Table 3 shows assignment of peptide sequences to differentiallyexpressed serum peptides. Peptides with significant differentialexpression (Table 2) were selected for tandem MS analyses. PrimaryMALDI-TOF MS spectra were reviewed to determine if the observed masseswere noise or if other peptide masses were occupying ±1.0 m/z TOF space(which would interfere with tandem MS data acquisition).

Table 4 shows assignment of additional peptide sequences todifferentially expressed serum peptides detected in CAD samples by highmass accuracy LCMS. Samples previously analyzed by MALDI-TOF MS-MS/MSmethods were analyzed by LCMS methods using a Thermo LTQ-Orbitrap XLplatform.

Table 5 shows application of receiver operator characteristic analysisto determine the ability of individual peptides (Table 4) to classifyCAR positive (case) and CAD negative (control) serum samples. Theabundances of individual serum peptides were estimated from LCMS datasets using extracted ion chromatograms. These areas were used for ROCcurve analysis. The ROC area under the curve (AUC) values, sensitivity,specificity, positive predictive value (PPV) and negative predictivevalue (NPV) are shown for each peptide.

BRIEF DESCRIPTION OF THE SEQUENCE LISTING

SEQ ID NOS: 1 and 7 are amino acid sequences of a portion of a humanfibrinogen alpha chain peptide.

SEQ ID NOS: 2 and 8 are amino acid sequences of another portion of ahuman fibrinogen alpha chain peptide.

SEQ ID NOS: 3 and 9 are amino acid sequences of a portion of atolloid-like 2 peptide.

SEQ ID NOS: 4 and 10 are amino acid sequences of a portion of a bonemorphogenetic protein-1 peptide.

SEQ ID NOS: 5 and 11 are amino acid sequences of a portion of aprotocadherin-20 peptide.

SEQ ID NOS: 6 and 12 are amino acid sequences of a portion of achondroitin beta-1,4-N-acetylgalactosaminyltransferase 2 peptide.

SEQ ID NOS: 13 to 30 are amino acid sequences of fibrinopeptides.

DETAILED DESCRIPTION

The details of one or more embodiments of the presently disclosedsubject matter are set forth in the accompanying description below.Other features, objects, and advantages of the presently disclosedsubject matter will be apparent from the detailed description, figures,and claims. All publications, patent applications, patents, and otherreferences mentioned herein are incorporated by reference in theirentirety. Some of the polynucleotide and polypeptide sequences disclosedherein are cross-referenced to GenBank, Swiss-Prot, or other publicdatabase accession numbers. The sequences cross-referenced in theGenBank, Swiss-Prot, or other public database are expressly incorporatedby reference as are equivalent and related sequences present in GenBank,Swiss-Prot, or other public databases. Also expressly incorporatedherein by reference are all annotations present in the GenBank,Swiss-Prot, or other public databases associated with the sequencesdisclosed herein. In case of conflict, the present specification,including definitions, will control.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood to one of ordinary skill inthe art to which the presently disclosed subject matter belongs.Although any methods, devices, and materials similar or equivalent tothose described herein can be used in the practice or testing of thepresently disclosed subject matter, representative methods, devices, andmaterials are now described.

Following long-standing patent law convention, the terms “a”, “an”, and“the” refer to “one or more” when used in this application, includingthe claims. Thus, for example, reference to “a cell” or “a virus”includes a plurality of such cells or viruses, respectively, and soforth.

Unless otherwise indicated, all numbers expressing quantities ofingredients, reaction conditions, and so forth used in the specificationand claims are to be understood as being modified in all instances bythe term “about”. Accordingly, unless indicated to the contrary, thenumerical parameters set forth in this specification and attachedexemplary claims are approximations that can vary depending upon thedesired properties sought to be obtained by the presently disclosedsubject matter.

As used herein, the term “about,” when referring to a value or to anamount of mass, weight, time, volume, concentration or percentage ismeant to encompass variations of in some embodiments ±20%, in someembodiments ±10%, in some embodiments ±5%, in some embodiments ±1%, insome embodiments ±0.5%, and in some embodiments ±0.1% from the specifiedamount, as such variations are appropriate to perform the disclosedmethod.

Cardiovascular diseases (CVDs) are a leading cause of disability anddeath in the developed world, resulting in more premature deaths thanany other illness. Unsurprisingly, treatment of CVD represents a veryhigh cost burden to any healthcare system. Accordingly, there istremendous social and political pressure to develop earlier and morereliable diagnostic tests to assist in the detection, treatment, andprevention of CVD. The presently disclosed subject matter providesmethods and compositions for diagnosing CVD, or the risk thereof, insubjects, as well as monitoring CVD treatment efficacy and diseaseprogression in the subjects.

Cardiovascular disease refers to the class of diseases that involve theheart and/or blood vessels (arteries and veins). CVD, as the term isused herein, can refer to any disease that affects the cardiovascularsystem, such as for example coronary artery disease (CAD) and peripheralvascular disease (PVD). These and other CVD conditions have relatedcauses, mechanisms, and treatments. In practice, CVD can be treated bycardiologists, thoracic surgeons, vascular surgeons, neurologists, andinterventional radiologists, depending on the organ system that is beingtreated. There is considerable overlap in the specialties, and it iscommon for certain procedures to be performed by different types ofspecialists in the same hospital.

“Peripheral vascular disease” (PVD) as used herein, also known asperipheral artery occlusive disease (PAOD) or peripheral artery disease(PAD), is a collator for multiple diseases caused by the obstruction oflarge peripheral arteries, which can result from atherosclerosis,inflammatory processes leading to stenosis, an embolism or thrombusformation. It can cause either acute or chronic ischemic.

“Coronary artery disease” (CAD) as used herein, also called coronaryheart disease (CHD), ischemic heart disease, and atherosclerotic heartdisease, is the end result of the accumulation of atheromatous plaqueswithin the walls of the arteries that supply the myocardium (the muscleof the heart). While the symptoms and signs of CAD are noted in theadvanced state of disease, most individuals with CAD show no symptoms ofdisease for decades even as the disease progresses. Unfortunately, thefirst onset of symptoms may be a “sudden” life-threatening heart attack.After decades of progression, some of these atheromatous plaques mayrupture and (along with the activation of the blood clotting system)start limiting blood flow to the heart muscle. The disease is a commoncause of sudden death and is also a very common reason for death of menand women over 65 years of age.

Thus, a subject may be afflicted with a CVD, such as for example CAD orPVD, for an extended time without an overt manifestation of symptoms. Assuch, the presently disclosed subject matter provides methods andpeptide biomarkers that can be utilized to diagnose or predict the riskof developing a CVD in a subject in advance of clinical manifestationsof the disease, thereby providing earlier treatment opportunities.

In some embodiments of the presently disclosed subject matter, a methodfor diagnosing a cardiovascular disease in a subject is provided. Insome embodiments, the method comprises obtaining a biological samplefrom the subject and determining an amount (including a qualitativedetermination of the presence or absence) of at least one peptidebiomarker associated with CVD, such as for example one or more peptidesset forth in SEQ ID NOS: 8-30. In some embodiments, the peptidebiomarkers comprise one or more peptides selected from the groupconsisting of protocadherin-20 (PCDH-20), tolloid-like 2 protein(TLL-2), mammalian tolloid protein (mTLD), bone morphogenetic protein-1(BMP-1), fibrinopeptide A (FPA, also known as fibrinogen α-chain),phosphorylated fibrinopeptide A (pFPA), chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2), andfragments thereof. The method can further comprise comparing the amountof the at least one peptide in the sample with a control level. If theamount determined from the sample differs from (e.g., is greater than oris less than) the control level, the subject can be diagnosed as having,or being at an increased risk of developing, the cardiovascular disease.

As one example, in some embodiments, a subject can be diagnosed ashaving, or at risk of developing, a CVD if biomarker levels in abiological sample from the subject for one or more of PCDH-20, TLL-2,mTLD, FPA, pFPA, and/or fragments thereof are increased as compared tocontrol levels. Alternatively, or in conjunction with increases in thesebiomarker levels, the subject can be diagnosed as having, or at risk ofdeveloping, a CVD if biomarker levels in a biological sample from thesubject for one or more of BMP-1, CSGalNAcT-2, and/or fragments thereofare decreased as compared to control levels.

In some particular embodiments, the biomarkers are measured from aparticular fraction of the biological sample. More specifically, in someparticular embodiments, the biomarkers are measured in a serum fractionof peptides bound to other peptides (e.g., albumin, immunoglobulins, orother abundant proteins). That is, the biomarker peptides are not freein whole serum, but rather are bound to one or more other proteinspresent in the serum. Biological samples can be fractionated using anyof several methodologies known in the art, including for example,immunodepletion strategies.

The terms “polypeptide”, “protein”, and “peptide”, which are usedinterchangeably herein, refer to a polymer of the 20 protein aminoacids, including modified amino acids (e.g., phosphorylated, glycated,etc.) and amino acid analogs, regardless of its size or function.Although “protein” is often used in reference to relatively largepolypeptides, and “peptide” is often used in reference to smallpolypeptides, usage of these terms in the art overlaps and varies. Theterm “peptide” as used herein refers to peptides, polypeptides, proteinsand fragments of proteins, unless otherwise noted. The terms “protein”,“polypeptide” and “peptide” are used interchangeably herein whenreferring to a gene product and fragments thereof. Thus, exemplarypolypeptides include gene products, naturally occurring proteins,homologs, orthologs, paralogs, fragments and other equivalents,variants, fragments, and analogs of the foregoing.

The terms “polypeptide fragment” or “fragment”, when used in referenceto a polypeptide, refers to a polypeptide in which amino acid residuesare absent as compared to the full-length polypeptide itself, but wherethe remaining amino acid sequence is usually identical to thecorresponding positions in the reference polypeptide. Such deletions canoccur at the amino-terminus or carboxy-terminus of the referencepolypeptide, or alternatively both. Fragments typically are at least 5,6, 8 or 10 amino acids long, at least 14 amino acids long, at least 20,30, 40 or 50 amino acids long, at least 75 amino acids long, or at least100, 150, 200, 300, 500 or more amino acids long.

A fragment can retain one or more of the biological activities of thereference polypeptide. In some embodiments, a fragment can comprise adomain or feature, and optionally additional amino acids on one or bothsides of the domain or feature, which additional amino acids can numberfrom 5, 10, 15, 20, 30, 40, 50, or up to 100 or more residues. Further,fragments can include a sub-fragment of a specific region, whichsub-fragment retains a function of the region from which it is derived.When the term “peptide” is used herein, it is intended to include thefull-length peptide as well as fragments of the peptide. Thus, anidentified fragment of a peptide (e.g., see Tables 2 and 3) is intendedto encompass the fragment as well as the full-length peptide. Forexample, when reference is made herein to antibodies specific for thepeptides of SEQ ID NOS: 8-30, it is intended that the antibodies canhave specificity for the peptide fragment and/or the full-length peptidefrom which it is derived.

The term “biological sample” as used herein refers to any body fluid ortissue potentially comprising one or more biomarkers associated withCVD. In some embodiments, for example, the biological sample can be asaliva sample, a blood sample, a serum sample, a plasma sample, a urinesample, or sub-fractions thereof.

The terms “diagnosing” and “diagnosis” as used herein refer to methodsby which the skilled artisan can estimate and even determine whether ornot a subject is suffering, or at risk of suffering from, a givendisease or condition. The skilled artisan often makes a diagnosis on thebasis of one or more diagnostic indicators, such as for example abiomarker, the amount (including presence or absence) of which isindicative of the development risk, presence, severity, or absence ofthe condition. Thus, “diagnosing” and “diagnosis” as used herein refersto determining presence and/or severity of a condition as well aspredicting a risk for developing the condition.

Along with diagnosis, clinical prognosis is also an area of greatconcern and interest. It is important to know the rate of progressionand severity of a disease in order to plan the most effective therapy.If a more accurate prognosis can be made, appropriate therapy, and insome instances less severe therapy for the patient can be chosen.Measurement of CVD biomarkers can be useful in order to separatesubjects with good prognosis who will need no further therapy from thosemore likely to develop severe disease and who might benefit from moreintensive treatments.

As such, “making a diagnosis” or “diagnosing”, as used herein, isfurther inclusive of making a prognosis, which can provide forpredicting a clinical outcome (with or without medical treatment),selecting an appropriate treatment (or whether treatment would beeffective), or monitoring a current treatment and potentially changingthe treatment, based on the measure of the peptide biomarkers disclosedherein.

In some embodiments of the presently disclosed subject matter, multipledetermination of one or more diagnostic or prognostic peptide biomarkerscan be made, and a temporal change in the biomarker can be used tomonitor the risk for development, development, or progression of diseaseand/or efficacy of appropriate therapies directed against the disease.In such an embodiment for example, one might expect to see a decrease oran increase in the peptide biomarker(s) over time prior to initiation ofand/or during the course of effective therapy. Thus, the presentlydisclosed subject matter provides in some embodiments a method fordetermining treatment efficacy and/or progression of a cardiovasculardisease in a subject. In some embodiments, the method comprisesdetermining an amount of at least one peptide biomarker associated witha CVD, such as for example at least one peptide of SEQ ID NOS: 8-30, inbiological samples collected from the subject at a plurality ofdifferent time points and comparing the amounts of the at least onepeptide in the samples collected at different time points. For example,a first time point can be selected prior to initiation of a treatmentand a second time point can be selected at some time after initiation ofthe treatment. One or more biomarker levels can be measured in each ofthe samples taken from different time points and qualitative and/orquantitative differences noted. A change in the amounts of the biomarkerlevels from the first and second samples can be correlated withdetermining treatment efficacy and/or progression of the disease in thesubject.

The terms “correlated” and “correlating,” as used herein in reference tothe use of diagnostic and prognostic biomarkers, refers to comparing thepresence or quantity of the biomarker in a subject to its presence orquantity in subjects known to suffer from, or known to be at risk of, agiven condition (e.g., a CVD); or in subjects known to be free of agiven condition, i.e. “normal individuals”. For example, a biomarkerlevel in a biological sample can be compared to a level known to beassociated with a specific type of CVD. The sample's biomarker level issaid to have been correlated with a diagnosis; that is, the skilledartisan can use the biomarker level to determine whether the subjectsuffers from a specific type of CVD, and respond accordingly.Alternatively, the sample's biomarker level can be compared to a controlmarker level known to be associated with a good outcome (e.g., theabsence of CVD), such as an average level found in a population ofnormal subjects.

In certain embodiments, a diagnostic or prognostic biomarker iscorrelated to a condition or disease by merely its presence or absence.In other embodiments, a threshold level of a diagnostic or prognosticbiomarker can be established, and the level of the indicator in asubject sample can simply be compared to the threshold level. In someembodiments, a threshold level for the presently disclosed biomarkersassociated with CVD is about 25 pg/mL, about 50 pg/mL, about 60 pg/mL,about 75 pg/mL, about 100 pg/mL, about 150 pg/mL, about 200 pg/mL, about300 pg/mL, about 400 pg/mL, about 500 pg/mL, about 600 pg/mL, about 750pg/mL, about 1000 pg/mL, or about 2500 pg/mL.

As noted, in some embodiments, multiple determinations of one or morediagnostic or prognostic biomarkers can be made, and a temporal changein the marker can be used to determine a diagnosis or prognosis. Forexample, a diagnostic marker can be determined at an initial time, andagain at a second time. In such embodiments, an increase or decrease(depending on biomarker measured) in the marker from the initial time tothe second time can be diagnostic of a particular type of CVD, or agiven prognosis. Likewise, a decrease in the marker from the initialtime to the second time can be indicative of a particular type of CVD,or a given prognosis. Furthermore, the degree of change of one or moremarkers can be related to the severity of CVD and future adverse events.

The skilled artisan will understand that, while in certain embodimentscomparative measurements can be made of the same diagnostic marker atmultiple time points, one can also measure a given marker at one timepoint, and a second marker at a second time point, and a comparison ofthese markers can provide diagnostic information.

The phrase “determining the prognosis” as used herein refers to methodsby which the skilled artisan can predict the course or outcome of acondition in a subject. The term “prognosis” does not refer to theability to predict the course or outcome of a condition with 100%accuracy, or even that a given course or outcome is predictably more orless likely to occur based on the presence, absence or levels of testbiomarkers. Instead, the skilled artisan will understand that the term“prognosis” refers to an increased probability that a certain course oroutcome will occur; that is, that a course or outcome is more likely tooccur in a subject exhibiting a given condition, when compared to thoseindividuals not exhibiting the condition. For example, in individualsnot exhibiting the condition (e.g., not expressing the biomarker(s) orexpressing at a reduced level), the chance of a given outcome may beabout 3%. In certain embodiments, a prognosis is about a 5% chance of agiven outcome, about a 7% chance, about a 10% chance, about a 12%chance, about a 15% chance, about a 20% chance, about a 25% chance,about a 30% chance, about a 40% chance, about a 50% chance, about a 60%chance, about a 75% chance, about a 90% chance, or about a 95% chance.

The skilled artisan will understand that associating a prognosticindicator with a predisposition to an adverse outcome is a statisticalanalysis. For example, a biomarker level (e.g., quantity of expressionin a sample) of greater than a control level in some embodiments cansignal that a subject is more likely to suffer from a CVD than subjectswith a level less than or equal to the control level, as determined by alevel of statistical significance. Additionally, a change in markerconcentration from baseline levels can be reflective of subjectprognosis, and the degree of change in marker level can be related tothe severity of adverse events. Statistical significance is oftendetermined by comparing two or more populations, and determining aconfidence interval and/or a p value. See, e.g., Dowdy and Wearden,Statistics for Research, John Wiley & Sons, New York, 1983, incorporatedherein by reference in its entirety. Preferred confidence intervals ofthe present subject matter are 90%, 95%, 97.5%, 98%, 99%, 99.5%, 99.9%and 99.99%, while preferred p values are 0.1, 0.05, 0.025, 0.02, 0.01,0.005, 0.001, and 0.0001.

In other embodiments, a threshold degree of change in the level of aprognostic or diagnostic biomarker can be established, and the degree ofchange in the level of the indicator in a biological sample can simplybe compared to the threshold degree of change in the level. A preferredthreshold change in the level for markers of the presently disclosedsubject matter is about 5%, about 10%, about 15%, about 20%, about 25%,about 30%, about 50%, about 75%, about 100%, and about 150%. In yetother embodiments, a “nomogram” can be established, by which a level ofa prognostic or diagnostic indicator can be directly related to anassociated disposition towards a given outcome. The skilled artisan isacquainted with the use of such nomograms to relate two numeric valueswith the understanding that the uncertainty in this measurement is thesame as the uncertainty in the marker concentration because individualsample measurements are referenced, not population averages.

Numerous methods and devices are well known to the skilled artisan forthe detection and analysis of the biomarker peptides of the presentlydisclosed subject matter. With regard to polypeptides or proteins insubject test samples, mass spectrometry and/or immunoassay devices andmethods can be used, although other methods are well known to thoseskilled in the art (for example, the measurement of marker RNA levels).See, e.g., U.S. Pat. Nos. 6,143,576; 6,113,855; 6,019,944; 5,985,579;5,947,124; 5,939,272; 5,922,615; 5,885,527; 5,851,776; 5,824,799;5,679,526; 5,525,524; and 5,480,792, each of which is herebyincorporated by reference in its entirety. These devices and methods canutilize labeled molecules in various sandwich, competitive, ornon-competitive assay formats, to generate a signal that is related tothe presence or amount of an analyte of interest. Additionally, certainmethods and devices, such as biosensors and optical immunoassays, can beemployed to determine the presence or amount of analytes without theneed for a labeled molecule. See, e.g., U.S. Pat. Nos. 5,631,171; and5,955,377, each of which is hereby incorporated by reference in itsentirety.

In certain embodiments of the presently disclosed subject matter, thebiomarker peptides are analyzed using an immunoassay. The presence oramount of a marker can be determined using antibodies or fragmentsthereof specific for each marker and detecting specific binding. Forexample, in some embodiments, the antibody specifically binds a peptideof SEQ ID NOS: 8-30, which is inclusive of antibodies that bind afull-length protein or fragments thereof.

The antibody can in some embodiments instead specifically bind a peptideassociated with a peptide of SEQ ID NOS: 8-30. For example, as shown inTable 2, some of the marker peptides are isolated from the biologicalfluid bound to one or more other peptides (e.g., bound toimmunoglobulins, albumin, or other highly abundant proteins), and soantibodies specific for the other peptides can be useful for isolatingand identifying the marker peptide(s) of interest. Further, in someembodiments, the antibody can have binding specificity for specificforms of marker peptides, such as for example phosphorylated andunphosphorylated forms of marker peptides, including but not limited toantibodies that are specific for either phosphorylated orunphosphorylated fibrinopeptide A.

Any antibody which effectively binds one or more peptide biomarkersdisclosed herein is within the scope of the presently-disclosed subjectmatter. This includes by way of example, polyclonal and monoclonalantibodies, recombinant antibodies, chimeric antibodies, humanizedantibodies, bispecific antibodies, single chain antibodies, antibodiesfrom different species (e.g., mouse, goat, rabbit, human, rat, bovine,etc.), anti-idiotypic antibodies, antibodies of different isotype (IgG,IgM, IgE, IgA, etc.), as well as fragments and derivatives thereof(e.g., (Fab)₂, Fab, Fv, Fab, 2(Fab), Fab′, (Fab′)₂ fragments). In someparticular embodiments, the antibody is a monoclonal antibody.

Any suitable immunoassay can be utilized, for example, enzyme-linkedimmunoassays (ELISA), radioimmunoassays (RIAs), competitive bindingassays, and the like. Specific immunological binding of the antibody tothe marker can be detected directly or indirectly. Direct labels includefluorescent or luminescent tags, metals, dyes, radionuclides, and thelike, attached to the antibody. Indirect labels include various enzymeswell known in the art, such as alkaline phosphatase, horseradishperoxidase and the like.

The use of immobilized antibodies or fragments thereof specific for thepeptide biomarkers is also contemplated by the present subject matter.The antibodies can be immobilized onto a variety of solid supports, suchas magnetic or chromatographic matrix particles, the surface of an assayplate (such as microtiter wells), pieces of a solid substrate material(such as plastic, nylon, paper), and the like. An assay strip can beprepared by coating the antibody or a plurality of antibodies in anarray on solid support. This strip can then be dipped into the testbiological sample and then processed quickly through washes anddetection steps to generate a measurable signal, such as for example acolored spot.

In some embodiments, a kit for the analysis of biomarkers is providedthat comprises antibodies having specificity for one or more biomarkersassociated with CVD. Such a kit can comprise devices and reagents forthe analysis of at least one test sample. The kit can further compriseinstructions for using the kit and conducting the analysis. Optionallythe kits can contain one or more reagents or devices for converting amarker level to a diagnosis or prognosis of the subject.

In some embodiments, mass spectrometry (MS) analysis can be used aloneor in combination with other methods (e.g., immunoassays) to determinethe presence and/or quantity of the one or more biomarkers of interestin a biological sample. In some embodiments, the MS analysis comprisesmatrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF)MS analysis, such as for example direct-spot MALDI-TOF or liquidchromatography MALDI-TOF mass spectrometry analysis. In someembodiments, the MS analysis comprises electrospray ionization (ESI) MS,such as for example liquid chromatography (LC) ESI-MS. Mass analysis canbe accomplished using commercially-available spectrometers, such as forexample triple quadrupole mass spectrometers. Methods for utilizing MSanalysis, including MALDI-TOF MS and ESI-MS, to detect the presence andquantity of biomarker peptides in biological samples are known in theart. See for example U.S. Pat. Nos. 6,925,389; 6,989,100; and 6,890,763for further guidance, each of which is incorporated by reference hereinin its entirety. In some embodiments, the sample can be acidified withacetic acid, for example, to control sample pH and also ionization ofweakly associated peptides off sample proteins prior to MS analysis.

The analysis of a plurality of markers can be carried out separately orsimultaneously with one test sample. Several markers can be combinedinto one test for efficient processing of a multiple of samples. Inaddition, one skilled in the art would recognize the value of testingmultiple samples (for example, at successive time points) from the samesubject. Such testing of serial samples will allow the identification ofchanges in biomarker levels over time. Increases or decreases in markerlevels, as well as the absence of change in marker levels, can provideuseful information about the disease status that includes, but is notlimited to identifying the approximate time from onset of the event, theappropriateness of various therapies, the effectiveness of varioustherapies, differentiation of the various types of CVD, identificationof the disease severity, and identification of the subject's outcome,including risk of future events.

A panel consisting of biomarkers associated with a CVD (e.g., thebiomarker peptides of SEQ ID NOS: 8-30) can be constructed to providerelevant information related to the diagnosis or prognosis of the CVDand management of subjects with the CVD. Such a panel can beconstructed, for example, using 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15 or 20individual biomarkers. The analysis of a single marker or subsets ofmarkers comprising a larger panel of markers could be carried out by oneskilled in the art to optimize clinical sensitivity or specificity invarious clinical settings. These include, but are not limited toambulatory, urgent care, critical care, intensive care, monitoring unit,insubject, outsubject, physician office, medical clinic, and healthscreening settings. Furthermore, one skilled in the art can use a singlemarker or a subset of markers comprising a larger panel of markers incombination with an adjustment of the diagnostic threshold in each ofthe aforementioned settings to optimize clinical sensitivity andspecificity. The clinical sensitivity of an assay is defined as thepercentage of those with the disease that the assay correctly predicts,and the specificity of an assay is defined as the percentage of thosewithout the disease that the assay correctly predicts (34).

The analysis of markers could be carried out in a variety of physicalformats as well. For example, the use of microtiter plates or automationcould be used to facilitate the processing of large numbers of testsamples. Alternatively, single sample formats could be developed tofacilitate immediate treatment and diagnosis in a timely fashion, forexample, in ambulatory transport or emergency room settings.

The presently disclosed subject matter further provides methods fortreating a cardiovascular disease in a subject. In some embodiments, themethods comprise administering to a subject an effective amount of afibrinopeptide A (FGA) polypeptide inhibitor molecule.

The term “effective amount” is used herein to refer to an amount of thetherapeutic composition (e.g., a composition comprising an FGAantagonist) sufficient to produce a measurable biological response(e.g., a reduction in a biological activity of FGA). Actual dosagelevels of active ingredients in a therapeutic composition of thepresently disclosed subject matter can be varied so as to administer anamount of the active compound(s) that is effective to achieve thedesired therapeutic response for a particular subject and/orapplication. The selected dosage level will depend upon a variety offactors including the activity of the therapeutic composition,formulation, the route of administration, combination with other drugsor treatments, severity of the condition being treated, and the physicalcondition and prior medical history of the subject being treated.Preferably, a minimal dose is administered, and dose is escalated in theabsence of dose-limiting toxicity to a minimally effective amount.Determination and adjustment of a therapeutically effective dose, aswell as evaluation of when and how to make such adjustments, are knownto those of ordinary skill in the art of medicine.

The term “inhibitor” refers to a chemical substance that inactivates ordecreases the biological activity of a polypeptide, such as FGA.

Suitable methods for administering to a subject a bioactive agent inaccordance with the methods of the present subject matter include butare not limited to systemic administration, parenteral administration(including intravascular, intramuscular, intraarterial administration),intranasal delivery, oral delivery, buccal delivery, subcutaneousadministration, inhalation, intratracheal installation, surgicalimplantation, transdermal delivery, local injection, and hyper-velocityinjection/bombardment. Where applicable, continuous infusion can enhancedrug accumulation at a target site (see, e.g., U.S. Pat. No. 6,180,082,incorporated herein by reference in its entirety).

The particular mode of administration used in accordance with themethods of the present subject matter depends on various factors,including but not limited to the bioactive agent and/or carrieremployed, the severity of the condition to be treated, and mechanismsfor metabolism or removal of the bioactive agent followingadministration.

For administration of a therapeutic composition as disclosed herein,conventional methods of extrapolating human dosage based on dosesadministered to a murine animal model can be carried out using theconversion factor for converting the mouse dosage to human dosage: DoseHuman per kg=Dose Mouse per kg×12 (35). Drug doses can also be given inmilligrams per square meter of body surface area because this method,rather than body weight, achieves a good correlation to certainmetabolic and excretionary functions. Moreover, body surface area can beused as a common denominator for drug dosage in adults and children aswell as in different animal species as described by Freireich et al.(35). Briefly, to express a mg/kg dose in any given species as theequivalent mg/sq m dose, multiply the dose by the appropriate km factor.In an adult human, 100 mg/kg is equivalent to 100 mg/kg×37 kg/sq m=3700mg/m².

For oral administration, a satisfactory result can be obtained employingthe FGA inhibitor in an amount ranging from about 0.01 mg/kg to about100 mg/kg and preferably from about 0.1 mg/kg to about 30 mg/kg. Apreferred oral dosage form, such as liquid suspensions, will contain thebioactive agent in an amount ranging from about 0.1 to about 500 mg,preferably from about 2 to about 50 mg, and more preferably from about10 to about 25 mg.

For additional guidance regarding formulation and dose, see references(36-45), each of which is incorporated herein by reference.

The formulations administered to the subject can take such forms asaerosols, suspensions, solutions or emulsions in oily or aqueousvehicles, and can contain formulatory agents such as suspending,stabilizing and/or dispersing agents. Alternatively, the bioactive agentcan be in powder form for constitution with a suitable vehicle, e.g.,sterile pyrogen-free water, before use. Further, in some embodiments,the bioactive agent can be formulated for impregnation in clothing orbarrier material, such as for example masks, gloves, surgical gowns,etc.

The formulations can be presented in unit-dose or multi-dose containers,for example sealed ampoules and vials, and can be stored in a frozen orfreeze-dried (lyophilized) condition requiring only the addition ofsterile liquid carrier immediately prior to use.

For oral administration, the compositions can take the form of, forexample, tablets or capsules prepared by a conventional technique withpharmaceutically acceptable excipients such as binding agents (e.g.,pregelatinized maize starch, polyvinylpyrrolidone or hydroxypropylmethylcellulose); fillers (e.g., lactose, microcrystalline cellulose orcalcium hydrogen phosphate); lubricants (e.g., magnesium stearate, talcor silica); disintegrants (e.g., potato starch or sodium starchglycollate); or wetting agents (e.g., sodium lauryl sulphate). Thetablets can be coated by methods known in the art.

Liquid preparations for oral or intranasal administration can take theform of, for example, aerosols, solutions, syrups or suspensions, orthey can be presented as a dry product for constitution with water orother suitable vehicle before use.

Such liquid preparations can be prepared by conventional techniques withpharmaceutically acceptable additives such as suspending agents (e.g.,sorbitol syrup, cellulose derivatives or hydrogenated edible fats);emulsifying agents (e.g. lecithin or acacia); non-aqueous vehicles(e.g., almond oil, oily esters, ethyl alcohol or fractionated vegetableoils); and preservatives (e.g., methyl or propyl-p-hydroxybenzoates orsorbic acid). The preparations can also contain buffer salts, flavoring,coloring and sweetening agents as appropriate. Preparations for oraladministration can be suitably formulated to give controlled release ofthe active compound. For buccal administration the compositions can takethe form of tablets or lozenges formulated in conventional manner.

The bioactive agents can also be formulated as a preparation forimplantation or injection. Thus, for example, the bioactive agents canbe formulated with suitable polymeric or hydrophobic materials (e.g., asan emulsion in an acceptable oil) or ion exchange resins, or assparingly soluble derivatives (e.g., as a sparingly soluble salt).

The bioactive agents can also be formulated in rectal compositions(e.g., suppositories or retention enemas containing conventionalsuppository bases such as cocoa butter or other glycerides), creams orlotions, or transdermal patches.

Formulations described herein can further comprise a pharmaceuticallyacceptable carrier. Suitable formulations include aqueous andnon-aqueous sterile injection solutions that can contain antioxidants,buffers, bacteriostats, bactericidal antibiotics and solutes that renderthe formulation isotonic with the bodily fluids of the intendedrecipient; and aqueous and non-aqueous sterile suspensions, which caninclude suspending agents and thickening agents. The pharmaceuticallyacceptable carriers or vehicles or excipients are well known to the oneskilled in the art. For example, a pharmaceutically acceptable carrieror vehicle or excipient can be a 0.9% NaCl (e.g., saline) solution or aphosphate buffer. The pharmaceutically acceptable carrier or vehicle orexcipients can be any compound or combination of compounds facilitatingthe administration of the bioactive agent; advantageously, the carrier,vehicle or excipient can facilitate administration, delivery and/orimprove preservation of the bioactive agent and/or non-infectious virus.

Further with respect to the methods of the presently disclosed subjectmatter, a preferred subject is a vertebrate subject. A preferredvertebrate is warm-blooded; a preferred warm-blooded vertebrate is amammal. A preferred mammal is most preferably a human. As used herein,the term “subject” includes both human and animal subjects. Thus,veterinary therapeutic uses are provided in accordance with thepresently disclosed subject matter.

As such, the presently disclosed subject matter provides for thetreatment and testing of mammals such as humans, as well as thosemammals of importance due to being endangered, such as Siberian tigers;of economic importance, such as animals raised on farms for consumptionby humans; and/or animals of social importance to humans, such asanimals kept as pets or in zoos. Examples of such animals include butare not limited to: carnivores such as cats and dogs; swine, includingpigs, hogs, and wild boars; ruminants and/or ungulates such as cattle,oxen, sheep, giraffes, deer, goats, bison, and camels; and horses. Alsoprovided is the treatment of birds, including the treatment of thosekinds of birds that are endangered and/or kept in zoos, as well as fowl,and more particularly domesticated fowl, i.e., poultry, such as turkeys,chickens, ducks, geese, guinea fowl, and the like, as they are also ofeconomic importance to humans. Thus, also provided is the testing andtreatment of livestock, including, but not limited to, domesticatedswine, ruminants, ungulates, horses (including race horses), poultry,and the like.

In some embodiments, the subject tested and/or treated is afflicted withor was previously afflicted with a disease other than CVD. Inparticular, the other disease can be a disease linked to or predisposingone to CVD. For example, in some embodiments, the subject is a diabeticsubject as diabetes can be a risk factor for developing CVD. Further, insome embodiments, the subject is suffering from an end stage renaldisease, which may be chronic or acute, and may be secondary to aprimary condition, including but not limited to diabetes, hypertension,lupus, nephrotic syndrome, polycystic kidney disease, interstitialnephritis, or cystinosis,

It will be understood that various details of the presently disclosedsubject matter can be changed without departing from the scope of thesubject matter. Furthermore, the foregoing description is for thepurpose of illustration only, and not for the purpose of limitation.

EXAMPLES

The following Examples have been included to illustrate modes of thepresently disclosed subject matter. In light of the present disclosureand the general level of skill in the art, those of skill willappreciate that the following Examples are intended to be exemplary onlyand that numerous changes, modifications, and alterations can beemployed without departing from the scope of the presently disclosedsubject matter.

The following examples may include compilations of data that arerepresentative of data gathered at various times during the course ofdevelopment and experimentation related to the presently-disclosedsubject matter.

Materials and Methods for Examples

Subject Characteristics.

Serum samples from 7 men without CAD and 11 men with CAD were evaluated.Seventy percent of the subjects were Caucasian. The two groups did notdiffer in age, hemoglobin, serum albumin, time on dialysis, or serumcholesterol (Table 1). The serum samples were obtained from storage in abiorepository at −80° C. All subjects had undergone cardiaccatheterization during evaluation for kidney transplantation. Subjectswere selected on the basis of the cardiac catheterizationinterpretation. CAD was defined as the presence of three vessel diseaseinvolvement and a description of severe CAD. The absence of CAD wasdefined as a normal catheterization study or minimal coronary arterydisease. The serum samples were obtained within one month of cardiaccatheterization. The study protocol was reviewed by the University ofLouisville Human Studies Committee.

TABLE 1 With CAD Without CAD Age (years) 42 ± 11 51 ± 8 Hemoglobin(g/dL) 11.9 ± 1.3  11.6 ± 1.7 Albumin (g/dL) 3.7 ± 0.4  3.8 ± 0.5Cholesterol (mg/dL) 184 ± 56  194 ± 67 Dialysis Duration (Days) 566 ±207  566 ± 342

Experimental Design:

An outline of the experimental workflow is provided in FIG. 7. Thesample selection, handling and acquisition of peptide profiling datawith MADLI-TOF MS were designed to minimize the introduction of bias indata analysis. All samples were assigned numbers randomly. Furtherrandomization occurred with the order of sample preparation, samplelyophilization, MALDI-TOF plate spotting, and TOF and TOF/TOF dataacquisition. Sample fractionation generated peptide panels consisting offree peptides, peptides that were bound to total serum proteins,peptides possibly released during the albumin/IgG immunodepletion, andpeptides selectively bound to the highly abundant proteins, albumin andIgG. Analysis of differentially expressed peptides was conducted usingPCA and Student's t-test, followed by manual review of ion intensitiesacross all ion lists. Manual review was performed to ensure thatpeptides were not excluded due to incorrect base line normalization orbaseline subtraction. Amino acid sequences construed from MALDI-TOF/TOFsequence tag analysis were validated using commercially synthesizedpeptides to recapitulate the MALDI-TOF/TOF analysis.

Sample Handling:

Samples were thawed once to aliquot into 100 μL volumes for furtherstorage at −80° C. and once for sample preparation for peptidequantification. Samples were analyzed using two separate aliquots andindividual aliquots were analyzed in triplicate. Serum samples weredepleted of albumin and IgG using commercially available affinity spincolumns (Sartorius N.A. Inc, Edgewood, N.Y.) according to themanufacturer's guidelines. Peptides not bound to serum proteins wereisolated using a modification of the precipitation method of Chertov etal (31). Peptides bound to albumin and IgG were recovered from the albumin/IgG affinity resin by acid stripping with 10% acetic acid. Peptidesbound to serum proteins were recovered from the organicsolvent-coagulated proteins by salt or acid ionization. Recoveredpeptide solutions were lyophilized and resuspended in 0.1%trifluoroacetic acid (TFA) prior to MALDI-TOF MS analysis.

Analysis of Serum Peptides Using MALDI-TOF MS.

All samples were desalted and concentrated for MALDI-TOF MS analysisusing C18 ZIPTIPS™ (Millipore, Billerica, Mass.). Peptides were elutedfrom the C18 resin using sample matrix, 5 mg/mL4-hydroxy-α-cyanocinnamic acid (α-CN), and directly spotted onto theMALDI plate. Triplicate samples of each aliquot were spotted onto aMALDI-TOF target plate in positions chosen at random to preventinstrument or operator bias during data collection. Positive ionMALDI-TOF mass spectra were acquired using an Applied BiosystemsProteomics Analyzer (Model AB4700, Foster City, Calif.) operating inreflectron mode and with ion source pressure ˜0.5 μTorr. After a 400 nstime-delayed ion extraction period, the ions were accelerated to 20 kVfor TOF mass spectrometric analysis. A total of 1000 laser shots (355 nmNd:YAG solid state laser operating at 200 Hz) were acquired and signalaveraged. MALDI-TOF spectra were exported as .t2d files for comparisonof peptide abundance by MARKERVIEW™ (Applied Biosystems). Peptidesselected for further studies were analyzed using the AB4700 in TOF/TOFmode and interpretation of fragmentation data using MASCOT™ (MatrixScience, Boston, Mass.) ver1.9.

Analysis of MALDI-TOF MS Data Sets by MARKERVIEW™ Software.

Data files (.t2d) were exported from the AB4700 Proteomics Analyzer andimported into MARKERVIEW™ software. This software can find spectralpeaks by user defined mass tolerance limits or bin spectra via userdefined bin sizes. In addition, the user may define minimum and maximumsignal responses, which assists in dealing with high-dimensional massspectral data sets. Data were analyzed using data binning, which allowedfor baseline subtraction. Following data import, the data werepreprocessed using no-weighting and either mean-centered or Pareto datascaling prior to PCA. Peptides that sorted into groups were compared byStudent's t-test to assess the statistical significance of thedifference between the two groups. Differentially expressed peptideswere selected for tandem MS analysis using the AB4700 ProteomicsAnalyzer.

Targeted LCMS Analysis of Selected Serum Peptides.

Aliquots (20 μL) of each sample from subjects with CAD were pooled andpeptides isolated as described above. The process was repeated forsamples from subjects without CAD. The isolated peptides were separatedusing nanoflow one-dimensional reversed phase chromatography and roboticfraction collection directly onto MALDI-TOF target plates. MADLI-TOFanalysis.

Immunoblot Analysis.

Immunoblotting was performed as previously described (32, 33). Fiftymicrograms of protein was subjected to 10% SDS-PAGE and immunoblotanalysis with an anti-BMP-1 antibody (1:2000, B5058, Sigma-Aldrich, St.Louis, Mo.) raised against a peptide from the N-terminal domain of BMP-1or anti-mTLD antibody (1:2000, AB81030, Chemicon International,Temecula, Calif.) raised against a peptide from the C-terminal domain ofmTLD. Highly abundant proteins were immunosubtracted (ProteoPrep 20Plasma Immunodepletion Kit, Sigma-Aldrich) from serum samples. Both highand low abundance serum protein fractions were used for immunoblotanalysis of BMP-1 and mTLD expression.

Statistical Analysis of Data.

Principal component analysis of mass spectra was performed usingMarkerView software. Differential peptide and protein expression wascompared by an unpaired, two-tailed Student's t-test using aligned MALDIspectra and the peak cluster area for individual peptides. A p value of<0.05 was considered significant.

Results of Examples Direct Analysis of Serum Peptide Abundance UsingMatrix Assisted Laser Desorption Ionization (MALDI)-Time of Flight (TOF)Mass Spectrometry (MS)

The purpose of these experiments was to determine if serum peptides weredifferentially expressed in the serum of diabetic men with ESRD and CADcompared to diabetic men with ESRD and no CAD. To enrich analytequantity and preserve any specific peptide interactions with intactproteins, serum samples were first fractionated to yield fourpeptide-containing fractions: unbound peptides present in whole serum;peptides bound to IgG and albumin; peptides released during depletion ofIgG and albumin; and, peptides bound to proteins present after IgG andalbumin depletion. Peptide expression data were first examined usingprincipal component analysis (PCA). PCA is a method of exploratory dataanalysis that reduces the complexity of data, while retaining theirvariability, by transforming the data into a new group of variables,referred to as the principal components. PCA was used to obtain anunbiased assessment of whether or not the MALDI-TOF MS peptideexpression data self-sorted into two groups corresponding to subjectswith and without CAD. As shown in FIG. 1, the peptide expression dataself sorted, suggesting differences in peptide expression betweensubjects with and without CAD.

To confirm this difference, the mass spectra from the subject sampleswas aligned and compared to the expression of each peptide between thetwo groups. Differences in expression of individual peptides wereevaluated using Student's t-test. These analyses resulted in theidentification of eight peptide masses whose expression wassignificantly different between the group of subjects with CAD and thegroup of subjects without CAD (Table 2 and FIGS. 2-4).

TABLE 2 Peptide Observed Statistical Group with Sample PeptideSignificance Increased Group Mass (p<) Expression Unbound 1896.015 0.025CAD Serum Peptides Whole- 740.313 0.01 CAD Serum- 1140.584 0.05 CADBound 1418.669 0.001 CAD Peptides 1465.665 0.025 CAD 1545.545 0.01 CAD1616.663 0.025 CAD 1991.892 0.001 No CAD

To ensure sufficient analyte for amino acid sequencing by tandem MS, twopools of serum were prepared, one containing an aliquot of serum fromeach subject in the group with CAD and the other containing an aliquotof serum from each subject in the group without CAD. Peptide sequencetagging by MALDI-TOF/TOF MS resulted in putative identifications forfive peptide masses derived from four gene products (Table 3). Thesepeptides were derived from a phosphorylated portion of the fibrinogenalpha chain 19-35 (pFPA) (¹⁸T.AD(pS)GEGDFLAEGGGVR.G³⁶; SEQ ID NO: 1), asecond sequence of the fibrinogen alpha chain 20-35(¹⁹A.DSGEGDFLAEGGGVR.G³⁶; SEQ ID NO: 2), tolloid-like 2 protein (TLL-2)729-741 (⁷²⁸H.FFSDKDECAKDN.G⁷⁴¹; SEQ ID NO: 3), or bone morphogeneticprotein-1 (BMP-1) 700-711 (⁶⁹⁹H.FFSDKDECSKDN.G⁷¹²; SEQ ID NO: 4),protocadherin-20 69-75 (⁶⁸S.AGRPDPQ.S⁷⁶; SEQ ID NO: 5), and chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2) 31-50(³⁰Y.LLECAPQTDG NASLPGWGE.N⁵¹; SEQ ID NO: 6). The sequence tag analysiscould not discern between TLL-2 and BMP-1 as they are highly homologousand the peptide sequences of interest differed by a single amino acid(10). To validate the peptide identifications, the fragmentation datafor the peptides was compared against fragmentation data forcommercially synthesized peptides having the amino acid sequencesreturned by MASCOT sequence tag analysis. Four of the five peptides weresuccessfully chemically synthesized and used to manually verifyassignment of peptide fragmentation data and to confirm the originalpeptide amino acid sequence assignments.

TABLE 3 Mass Accession Proposed Amino Post-translational SEQ IDProtein Name (m/z) No. Gene Name Acid Sequence modification NOS:Chondroitin beta-1,4- 1991.896 Q8N6G5 CGAT2_HUMANY.LLECAPQTDG NASLPGVVGE.N 6 (12) N-acetylgalactos- aminyltransferase 2Fibrinogen α-chain 1616.663 P02671 FIBA_HUMAN T.AD(pS)GEGDFLAE GGGVR.GPhosphorylation 1 (7) Fibrinogen α-chain 1465.675 P02671 FIBA_HUMANA.DSGEGDFLAE GGGVR.G 2 (8) Tolloid-like 2 protein 1418.669 Q9Y6L7TLL-2_HUMAN H.FFSDKDECAK DN.G 3 (9) or or or Bone morphogenetic P13497BMP1_HUMAN protein-1 Protocadherin-20 740.313 Q8N6Y1 PCD20_HUMANS.AGRPDPQ.S 5 (11) *First and last amino acids in the presented sequenceare separated from the candidate peptide sequence by periods. The aminoacid sequence contained within these bracketing amino acids (SEQ ID NOS:7-12) is the proposed amino acid sequence for the peptide biomarker.Parentheses surrounding a particular residue denotes a posttranslationalmodification as indicated.

Analysis of Serum Peptide Abundance Using Liquid Chromatography-MassSpectrometry

Initial efforts to identify serum peptides that were associated withCAD+ or CAD− samples were conducted using a pure discovery MALDI-TOF MSproteomic approach. The findings from those studies identifieddifferential abundances of various fibrinopeptides andphosphofibrinopeptides (Table 3), and those peptides were found to bemore abundant in CAD+ samples. Those MALDI-TOF MS studies were thenfollowed in a repeat analysis of bio-reposited samples using a targetedproteomic and accurate mass liquid chromatography-mass spectrometrymethods (LC-LTQ-Orbitrap XL) to detect and quantify a large series offibrinopeptides and phosphofibrinopeptides. Briefly, a stable isotopelabeled fibrinopepide (fibrinopeptide A) was commercially synthesizedand included in the LCMS analyses for use as an internal standard. Theabundances for those peptides was estimated using the ratio of theextracted ion chromatograms for the observed endogenous peptide to theinternal standard fibrinopeptide and then using the previous casecontrol designations were analyzed for the ability to classify serumsamples as CAD+ or CAD−. Eighteen peptides were observed to demonstrateincreased mean abundance in CAD+ serum samples (Table 4). One peptide ofthe twenty had marginally different abundance between CAD+ and CAD−samples. One peptide demonstrated a slight decrease in CAD+ samples. Acomparison by student's t-test of the summed normalized fibrinopeptideabundance for all 20 peptides between case and control gave a p-value of0.082. Those data supported the application of high serum fibrinopeptideabundance as a candidate biomarker for coronary artery disease indiabetics with end-stage renal disease (see, e.g., Table 5).

TABLE 4 SEQ ID NO: Peptide Sequence [M + 1H]1+ [M + 2H]2+ 7 FP-AADSGEGDFLAEGGGVR 768.850 13 FP-A-p AD(pS) 808.833 GEGDFLAEGGGVR 8 A-1-1DSGEGDFLAEGGGVR 733.331 14 A-1-1-p D(pS) 773.314 GEGDFLAEGGGVR 15 A-1-2SGEGDFLAEGGGVR 675.818 16 A-1-3 GEGDFLAEGGGVR 632.302 17 A-1-4EGDFLAEGGGVR 603.791 18 A-1-6 DFLAEGGGVR 510.759 19 A-1-7 FLAEGGGVR453.246 20 A-2-0 ADSGEGDFLAEGGGV 690.799 21 A-2-0-p AD(pS) 1460.558730.782 GEGDFLAEGGGV 22 A-2-1 DSGEGDFLAEGGGV 1309.554 655.281 23 A-2-1-pD(pS) 695.264 GEGDFLAEGGGV 24 A-2-2 SGEGDFLAEGGGV 1194.527 597.767 25A-2-3 GEGDFLAEGGGV 1107.495 554.251 26 A-2-4 EGDFLAEGGGV 1050.474525.741 27 A-2-5 GDFLAEGGGV 921.431 461.219 28 A-2-6 DFLAEGGGV 864.41029 A-2-7 FLAEGGGV 749.383 30 A-2-8 LAEGGGV 602.314

TABLE 5 Name AUC Sensitivity Specificity PPV NPV A-2-5 0.734 0.538 0.9090.856 0.663 A-2-7 0.727 0.538 0.909 0.856 0.663 A-2-6 0.720 0.923 0.4550.629 0.855 A-2-8 0.713 0.769 0.455 0.585 0.663 FP-A 0.699 0.538 0.9090.856 0.663 A-2-0 0.699 0.462 0.909 0.835 0.628 A-2-4 0.699 0.538 0.9090.856 0.663 A-2-3 0.685 0.462 0.909 0.835 0.628 A-1-1 0.675 0.538 0.9090.856 0.663 A-1-2 0.664 0.615 0.818 0.772 0.680 A-1-4 0.661 0.615 0.8180.772 0.680 A-2-0-p 0.661 0.538 0.909 0.856 0.663 FP-A-p 0.657 0.4620.909 0.835 0.628 A-1-6 0.657 0.538 0.909 0.856 0.663 A-2-1 0.657 0.5380.909 0.856 0.663 A-2-2 0.650 0.615 0.909 0.871 0.703 A-1-3 0.650 0.6150.909 0.871 0.703 A-1-7 0.650 0.769 0.727 0.738 0.759 A-2-1-p 0.5870.615 0.909 0.871 0.703 A-1-1-p 0.580 0.462 1.000 1.000 0.650

Immunoblot Analysis of Mammalian Tolloid Protein (mTLD) and BMP-1

The presence of increased amounts of specific peptide fragments was thenexamined to determine if it might reflect changes in the amount of thecorresponding intact protein. Immunoblots of mTLD and BMP-1 in wholeserum were initially performed and no difference was found in expressionbetween subjects with and without CAD. With the intent to decrease thedynamic range of protein concentrations, the samples were depleted ofthe twenty most abundant proteins using a commercial affinity column(ProteoPrep 20 Plasma Immunodepletion Kit, Sigma-Aldrich). Immunoblotfor mTLD and BMP-1 of the low abundance serum fraction again showed nodifference between the groups. Because BMP-1 can bind to abundant plasmaproteins such as alpha-2 macroglobulin,(11) the fraction removed by theimmunoaffinity column for both mTLD and BMP-1 was then immunoblotted.Protein bound mTLD was significantly increased in serum from subjectswith CAD compared to subjects without CAD (FIG. 5), while protein-boundBMP-1 expression was significantly decreased (FIG. 6).

Discussion of the Examples

Cardiovascular diseases are the major cause of mortality in the generalpopulation, but even more so in subpopulations with significantunderlying health issues, including in particular subjects with chronickidney disease. The failure of traditional risk factors for the generalpopulation to fully explain the risk of CVDs in subpopulations has ledto a search for alternative, or non-traditional, risk factors.

A large number of individual biomarkers of coronary heart disease in thegeneral population have been proposed, including C-reactive protein(CRP),(12) homocysteine,(13, 14) fibrinogen,(15) and fibrin fragmentD-dimer (16). To date, incorporation of these non-traditional riskfactors into the algorithms used to assess risk of CVDs such as CAD hasnot markedly improved risk prediction in the general population, asdemonstrated by Wang and colleagues who found only a small increase inthe ability to classify risk when 10 biomarkers were used in amultivariate analysis adjusted for the conventional risk factors (17).Risk prediction for CVDs in hemodialysis subjects is even more fraughtwith difficulty. Both traditional and new risk assessment tools may notpredict CVDs in hemodialysis subjects. Recently, Weiner et al reportedthat the Framingham Risk Assessment Instrument performed poorly inpredicting cardiovascular events in subjects with chronic kidney disease(18). Furthermore, some specific biomarkers that are thought to predictdisease in the general population may not be as predictive inhemodialysis subjects. For example, C-reactive protein and interleukin-6may not be good surrogates for all inflammatory cardiovascular riskfactors in hemodialysis subjects (19). Finally, chronic kidney diseaseitself may be an independent risk factor for cardiovascular diseases(20). Clearly, improved methods to assess CVDs in the general populationand subpopulations (e.g., renal subjects) are needed.

One objective of the present examples was to determine if there arepeptides in biological samples that can discriminate between subjectshaving no significant CVD and those with significant CAD. In theseexamples, subjects were limited to diabetic subjects with ESRD having nosignificant CAD and those with significant CAD to control for variablesbetween subjects and because this subpopulation suffersdisproportionately from CVDs. It was further reasoned that, if suchdiscriminating peptides could be identified, they could provide newinsights into the pathophysiology of CVDs, and CAD in particular, inESRD and in diabetes. The present examples identified 8 peptides thatare differentially expressed in the serum of individuals that havedeveloped CAD as compared to well-matched controls. Of the eightpeptides, the protein from which these peptides were derived wasidentified in five instances.

The peptides were isolated from four serum fractions before MS analysisas outlined in the Methods and Results of the present examples. Thepeptide fractions isolated were unbound peptides present in whole serum,peptides bound to the IgG and albumin fraction, peptides released duringdepletion of IgG and albumin, and peptides bound to proteins presentafter IgG and albumin depletion. The rationale for this approach wasbased in part that the dynamic range of protein concentrations in serumis greater than 10¹², a range that exceeds the dynamic range ofdetection by MS. Isolation of peptides into sub-groups can decrease thedynamic range of expression and enrich analytes for characterization.

The eight candidate peptide biomarkers were identified using apeptidomic approach. Peptidomics can be defined as the quantitative andqualitative study of peptides expressed within a given biological systemin a time dependent fashion. Peptidomic studies typically use a top-downmass spectrometric analysis in that no enzymatic or proteolyticalterations are needed prior to MS interrogation. Recently,high-resolution, top-down MS methods, as employed in the present study,have been successfully applied to the diagnosis of disease. Theseanalytical tools, which include capillary electrophoresis (CE),electrospray ionization (ESI), and LC-MALDI-TOF MS, have been used toisolate endogenous peptides from serum, plasma and urine that predictclinical outcomes in congenital disorders or are diagnostic ofmalignancy (25-27). The same approaches have been applied to thediscovery of biomarker candidates of CAD (28). Recently, Zimmerli et alused CE coupled to ESI-MS to identify urinary polypeptides predictive ofCAD (29). The majority of the candidate CAD peptide biomarkersidentified by Zimmerli et al were derived from collagen. Donahue et alused LC coupled to ESI-MS to analyze the low molecular weight proteinfraction (less than 20 kDa) present in plasma from subjects with andwithout CAD (30). Individual plasma samples were pooled in their studyto enrich the low molecular weight fraction. They observed differentialexpression of 95 peptides between the two groups. There is littleoverlap between the findings herein and those of Donahue et al. Thislack of agreement may be a result of the differences between the twostudies in sample handling, pooling of samples, or the mass spectrometryapproach used.

The present examples examined whether serum peptide fragments reflectchanges in intact proteins. These peptide data had indicated increasedexpression of a fragment of either TLL-2 or BMP-1 in serum from subjectswith CAD. Because BMP-1, mTLD, TLL-1 and TLL-2 are very homologous,additional immunoblots were first performed with an antibody thatrecognizes mTLD, TLL-1 and TLL-2, but not BMP-1. These studies showedincreased expression of mTLD, but not TLL-1 and TLL-2 in serum fromsubjects with CAD (FIG. 5). Immunoblots of serum were then performedusing an antibody that recognizes the N-terminal peptide region inBMP-1. The 88 kDa band migrating with the BMP-1 positive control wasincreased in serum from subjects without CAD (FIG. 6). Furthermore, onlyprotein bound BMP-1 and mTLD were significantly different betweenclinical groups. No difference in unbound BMP-1 or mTLD expression wasseen between subjects with and without CAD.

In summary, the present examples provide data identifying a series ofbiomarkers for CVD in biological samples from a cohort ofwell-characterized subjects. The presently-disclosed data demonstratethat proteins from which these peptides are derived exhibit changes thatmay reflect alterations of intact serum protein concentrations. Thus,these peptides can serve as biomarkers for CVDs.

REFERENCES

-   1. Ohtake T, Kobayashi S, Moriya H, et al.: High prevalence of    occult coronary artery stenosis in subjects with chronic kidney    disease at the initiation of renal replacement therapy: an    angiographic examination. J Am Soc Nephrol 16:1141-1148, 2005-   2. Hase H, Joki N, Ishikawa H, et al.: Independent risk factors for    progression of coronary atherosclerosis in hemodialysis subjects.    Ther Apher Dial 10:321-327, 2006-   3. Hase H, Tsunoda T, Tanaka Y, et al.: Risk factors for de novo    acute cardiac events in subjects initiating hemodialysis with no    previous cardiac symptom. Kidney Int 70:1142-1148, 2006-   4. Parekh R S, Zhang L, Fivush B A, et al.: Incidence of    atherosclerosis by race in the dialysis morbidity and mortality    study: a sample of the US ESRD population. J Am Soc Nephrol    16:1420-1426, 2005-   5. Trespalacios F C, Taylor A J, Agodoa L Y, et al.: Incident acute    coronary syndromes in chronic dialysis subjects in the United    States. Kidney Int 62:1799-1805, 2002-   6. Herzog C A, Ma J Z, Collins A J: Poor long-term survival after    acute myocardial infarction among subjects on long-term dialysis. N    Engl J Med 339:799-805, 1998-   7. Charytan D, Mauri L, Agarwal A, et al.: The use of invasive    cardiac procedures after acute myocardial infarction in long-term    dialysis subjects. Am Heart J 152:558-564, 2006-   8. Zager P G, Nikolic J, Brown R H, et al.: “U” curve association of    blood pressure and mortality in hemodialysis subjects. Medical    Directors of Dialysis Clinic, Inc. Kidney Int 54:561-569, 1998-   9. Liu Y, Coresh J, Eustace J A, et al.: Association between    cholesterol level and mortality in dialysis subjects: role of    inflammation and malnutrition. Jama 291:451-459, 2004-   10. Scott I C, Blitz I L, Pappano W N, et al.: Mammalian    BMP-1/Tolloid-related metalloproteinases, including novel family    member mammalian Tolloid-like 2, have differential enzymatic    activities and distributions of expression relevant to patterning    and skeletogenesis. Dev Biol 213:283-300, 1999-   11. Zhang Y, Ge G, Greenspan D S: Inhibition of bone morphogenetic    protein 1 by native and altered forms of alpha2-macroglobulin. J    Biol Chem 281:39096-39104, 2006-   12. Cushman M, Arnold A M, Psaty B M, et al.: C-reactive protein and    the 10-year incidence of coronary heart disease in older men and    women: the cardiovascular health study. Circulation 112:25-31, 2005-   13. Mangoni A A, Jackson S H: Homocysteine and cardiovascular    disease: current evidence and future prospects. Am J Med    112:556-565, 2002-   14. Danesh J, Lewington S, Thompson S G, et al.: Plasma fibrinogen    level and the risk of major cardiovascular diseases and nonvascular    mortality: an individual participant meta-analysis. Jama    294:1799-1809, 2005-   15. Danesh J, Collins R, Appleby P, et al.: Association of    fibrinogen, C-reactive protein, albumin, or leukocyte count with    coronary heart disease: meta-analyses of prospective studies. Jama    279:1477-1482, 1998-   16. Danesh J, Whincup P, Walker M, et al.: Fibrin D-dimer and    coronary heart disease: prospective study and meta-analysis.    Circulation 103:2323-2327, 2001-   17. Wang T J, Gona P, Larson M G, et al.: Multiple biomarkers for    the prediction of first major cardiovascular events and death. N    Engl J Med 355:2631-2639, 2006-   18. Weiner D E, Tighiouart H, Elsayed E F, et al.: The Framingham    predictive instrument in chronic kidney disease. J Am Coll Cardiol    50:217-224, 2007-   19. Kaysen G A, Levin N W, Mitch W E, et al.: Evidence that    C-reactive protein or IL-6 are not surrogates for all inflammatory    cardiovascular risk factors in hemodialysis subjects. Blood Purif    24:508-516, 2006-   20. Go A S, Chertow G M, Fan D, et al.: Chronic kidney disease and    the risks of death, cardiovascular events, and hospitalization. N    Engl J Med 351:1296-1305, 2004-   21. Lopez M F, Mikulskis A, Kuzdzal S, et al.: A novel,    high-throughput workflow for discovery and identification of serum    carrier protein-bound peptide biomarker candidates in ovarian cancer    samples. Clin Chem 53:1067-1074, 2007-   22. Kuzdzal S, Lopez M, Mikulskis A, et al.: Biomarker discovery and    analysis platform: application to Alzheimer's disease. Biotechniques    39:606-607, 2005-   23. Petricoin E F, Belluco C, Araujo R P, et al.: The blood    peptidome: a higher dimension of information content for cancer    biomarker discovery. Nat Rev Cancer 6:961-967, 2006-   24. Lowenthal M S, Mehta A I, Frogale K, et al.: Analysis of    albumin-associated peptides and proteins from ovarian cancer    subjects. Clin Chem 51:1933-1945, 2005-   25. Villanueva J, Martorella A J, Lawlor K, et al.: Serum peptidome    patterns that distinguish metastatic thyroid carcinoma from    cancer-free controls are unbiased by gender and age. Mol Cell    Proteomics 5:1840-1852, 2006-   26. Villanueva J, Philip J, Chaparro C A, et al.: Correcting common    errors in identifying cancer-specific serum peptide signatures. J    Proteome. Res. 4:1060-1072, 2005-   27. Decramer S, Wittke S, Mischak H, et al.: Predicting the clinical    outcome of congenital unilateral ureteropelvic junction obstruction    in newborn by urinary proteome analysis. Nat Med 12:398-400, 2006-   28. Martin-Ventura J L, Blanco-Colio L M, Tunon J, et al.:    Proteomics in atherothrombosis: a future perspective. Expert Rev    Proteomics 4:249-260, 2007-   29. Zimmerli L U, Schiffer E, Zurbig P, et al.: Urinary proteomic    biomarkers in coronary artery disease. Mol Cell Proteomics, 2007-   30. Donahue M P, Rose K, Hochstrasser D, et al.: Discovery of    proteins related to coronary artery disease using industrial-scale    proteomics analysis of pooled plasma. Am Heart J 152:478-485, 2006-   31. Chertov O, Biragyn A, Kwak L W, et al.: Organic solvent    extraction of proteins and peptides from serum as an effective    sample preparation for detection and identification of biomarkers by    mass spectrometry. Proteomics 4:1195-1203, 2004-   32. Rane M J, Pan Y, Singh S, et al.: Heat shock protein 27 controls    apoptosis by regulating Akt activation. J. Biol. Chem.    278:27828-27835, 2003-   33. Rane M J, Gozal D, Butt W, et al.: Gamma-amino butyric acid type    B receptors stimulate neutrophil chemotaxis during    ischemia-reperfusion. J. Immunol. 174:7242-7249, 2005-   34. Tietz Textbook of Clinical Chemistry, 2nd edition, Carl Burtis    and Edward Ashwood eds., W.B. Saunders and Company, p. 496-   35. Freireich et al., (1966) Cancer Chemother Rep. 50:219-244-   36. U.S. Pat. No. 5,326,902-   37. U.S. Pat. No. 5,234,933-   38. PCT International Publication No. WO 93/25521-   39. Berkow et al., (1997) The Merck Manual of Medical Information,    Home ed. Merck Research Laboratories, Whitehouse Station, N.J.-   40. Goodman et al., (1996) Goodman & Gilman's the Pharmacological    Basis of Therapeutics, 9th ed. McGraw-Hill Health Professions    Division, New York-   41. Ebadi, (1998) CRC Desk Reference of Clinical Pharmacology. CRC    Press, Boca Raton, Fla.-   42. Katzung, (2001) Basic & Clinical Pharmacology, 8th ed. Lange    Medical Books/McGraw-Hill Medical Pub. Division, New York-   43. Remington et al., (1975) Remington's Pharmaceutical Sciences,    15th ed. Mack Pub. Co., Easton, Pa.-   44. Speight et al., (1997) Avery's Drug Treatment: A Guide to the    Properties, Choice, Therapeutic Use and Economic Value of Drugs in    Disease Management, 4th ed. Adis International,    Auckland/Philadelphia-   45. Duch et al., (1998) Toxicol. Lett. 100-101:255-263

It will be understood that various details of the presently disclosedsubject matter can be changed without departing from the scope of thepresently disclosed subject matter. Furthermore, the foregoingdescription is for the purpose of illustration only, and not for thepurpose of limitation.

What is claimed is:
 1. A method for diagnosing a cardiovascular diseasein a subject, comprising: (a) determining an amount of at least onepeptide having an amino acid sequence selected from the group consistingof SEQ ID NOS: 8-30; and (b) comparing the amount of the at least onepeptide in the sample with a control level, wherein if the amountdetermined in (a) is different than the control level, the subject isdiagnosed as having, or at an increased risk of developing, thecardiovascular disease.
 2. The method of claim 1, wherein determiningthe amount of the at least one peptide comprises determining the amountof the at least one peptide in the sample using mass spectrometry (MS)analysis, immunoassay analysis, or both.
 3. The method of claim 2,wherein the MS analysis comprises matrix-assisted laserdesorption/ionization (MALDI) time-of-flight (TOF) MS analysis orelectrospray ionization (ESI) MS.
 4. The method of claim 3, wherein theMALDI-TOF MS analysis is direct-spot MALDI-TOF or liquid chromatographyMALDI-TOF mass spectrometry analysis.
 5. The method of claim 2, whereinthe immunoassay analysis comprises an enzyme-linked immunosorbent assay(ELISA).
 6. The method of claim 1, wherein the at least one peptide isisolated from a fraction of the sample selected from the groupconsisting of a bound fraction and an unbound fraction.
 7. The method ofclaim 6, wherein the bound fraction is a fraction selected from thegroup consisting of an albumin-bound fraction and animmunoglobulin-bound fraction.
 8. The method of claim 1, wherein the atleast one peptide comprises one or more peptides selected from the groupconsisting of protocadherin-20 (PCDH-20), tolloid-like 2 protein(TLL-2), mammalian tolloid protein (mTLD), bone morphogenetic protein-1(BMP-1), phosphorylated fibrinopeptide A, chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2), andfragments thereof.
 9. The method of claim 1, wherein the at least onepeptide is a plurality of peptides.
 10. The method of claim 1, whereinthe sample is selected from the group consisting of a saliva sample, ablood sample, a serum sample, a plasma sample, and a urine sample. 11.The method of claim 1, wherein the subject is human.
 12. The method ofclaim 1, wherein the subject is a diabetic subject.
 13. The method ofclaim 1, wherein the cardiovascular disease is a coronary artery disease(CAD), a peripheral vascular disease, or both.
 14. The method of claim13, wherein the CAD comprises atherosclerosis.
 15. A method fordetermining treatment efficacy and/or progression of a cardiovasculardisease in a subject, comprising: (a) determining an amount of at leastone peptide having an amino acid sequence selected from the groupconsisting of SEQ ID NOS: 8-30 in a first biological sample collectedfrom the subject at a first time point; (b) determining an amount of theat least one peptide in a second biological sample from the subject at asecond time point; and (c) comparing the amounts of the at least onepeptide in the first and second samples, wherein a change in the amountsof the at least one peptide from the first and second samples iscorrelated with determining treatment efficacy and/or progression of thecardiovascular disease in the subject.
 16. The method of claim 15,wherein determining the amount of the at least one peptide in the firstand second biological samples comprises quantitating the amount of theat least one peptide in the samples using mass spectrometry (MS)analysis, immunoassay analysis, or both.
 17. The method of claim 16,wherein the MS analysis comprises matrix-assisted laserdesorption/ionization (MALDI) time-of-flight (TOF) MS analysis orelectrospray ionization (ESI) MS.
 18. The method of claim 17, whereinthe MALDI-TOF MS analysis is direct-spot MALDI-TOF or liquidchromatography MALDI-TOF mass spectrometry analysis.
 19. The method ofclaim 16, wherein the immunoassay analysis comprises an enzyme-linkedimmunosorbent assay (ELISA).
 20. The method of claim 15, wherein the atleast one peptide is isolated from a fraction of the sample selectedfrom the group consisting of a bound fraction and an unbound fraction.21. The method of claim 20, wherein the bound fraction is a fractionselected from the group consisting of an albumin-bound fraction and animmunoglobulin-bound fraction.
 22. The method of claim 15, wherein theat least one peptide comprises one or more peptides selected from thegroup consisting of protocadherin-20 (PCDH-20), tolloid-like 2 protein(TLL-2), mammalian tolloid protein (mTLD), bone morphogenetic protein-1(BMP-1), phosphorylated fibrinopeptide A, chondroitinbeta-1,4-N-acetylgalactosaminyltransferase 2 (CSGalNAcT-2), andfragments thereof.
 23. The method of claim 15, wherein the at least onepeptide is a plurality of peptides.
 24. The method of claim 15, whereinin the first and second biological samples are independently selectedfrom the group consisting of a saliva sample, a blood sample, a serumsample, a plasma sample, and a urine sample.
 25. The method of claim 15,wherein the subject is human.
 26. The method of claim 15, wherein thesubject is a diabetic subject.
 27. The method of claim 15, wherein thecardiovascular disease is a coronary artery disease (CAD), a peripheralvascular disease, or both.
 28. The method of claim 27, wherein the CADcomprises atherosclerosis.
 29. The method of claim 15, wherein the firsttime point is prior to initiation of a treatment for the cardiovasculardisease and the second time point is after initiation of the treatment.30. The method of claim 15, wherein the first time point is prior toonset of the cardiovascular disease and the second time point is afteronset of the cardiovascular disease.
 31. A method for treating acardiovascular disease in a subject, comprising administering to thesubject an effective amount of a fibrinopeptide A (FGA) polypeptideinhibitor molecule.
 32. The method of claim 31, wherein the subject ishuman.
 33. The method of claim 31, wherein the subject is a diabeticsubject.
 34. The method of claim 31, wherein the cardiovascular diseaseis a coronary artery disease (CAD), a peripheral vascular disease, orboth.
 35. The method of claim 34, wherein the CAD comprisesatherosclerosis.
 36. An antibody or fragment thereof that specificallyrecognizes: (a) a peptide having an amino acid sequence selected fromthe group consisting of SEQ ID NOS: 8-30; (b) a peptide associated witha peptide having an amino acid sequence selected from the groupconsisting of SEQ ID NOS: 8-30; or (c) both (a) and (b).
 37. Theantibody of claim 36, wherein said antibody is a monoclonal antibody.38. A kit for detecting cardiovascular disease, or a risk thereof, in asubject, the kit comprising one or more antibodies of claim
 36. 39. Thekit of claim 38, wherein the antibody is bound to a substrate.
 40. Thekit of claim 38, comprising instructions for using the kit.
 41. The kitof claim 38, wherein the subject is human.
 42. The kit of claim 38,wherein the subject is a diabetic subject.
 43. The kit of claim 38,wherein the cardiovascular disease is a coronary artery disease (CAD), aperipheral vascular disease, or both.
 44. The kit of claim 43, whereinthe CAD comprises atherosclerosis.
 45. The kit of claim 43, wherein theone or more antibodies is a plurality of different antibodies.